High-dimensional learning of linear causal networks via inverse covariance estimation

We establish a new framework for statistical estimation of directed acyclic graphs (DAGs) when data are generated from a linear, possibly non-Gaussian structural equation model. Our framework consists of two parts: (1) inferring the moralized graph from the support of the inverse covariance matrix; and (2) selecting the best-scoring graph amongst DAGs that are consistent with the moralized graph. We show that when the error variances are known or estimated to close enough precision, the true DAG is the unique minimizer of the score computed using the reweighted squared l_2-loss. Our population-level results have implications for the identifiability of linear SEMs when the error covariances are specified up to a constant multiple. On the statistical side, we establish rigorous conditions for high-dimensional consistency of our two-part algorithm, defined in terms of a "gap" between the true DAG and the next best candidate. Finally, we demonstrate that dynamic programming may be used to select the optimal DAG in linear time when the treewidth of the moralized graph is bounded.Comment: 41 pages, 7 figure

The Transatlantic Productivity Gap: Is R&D the Main Culprit?

The literature has pointed to different causes to explain the productivity gap between Europe and United States in the last decades. This paper tests the hypothesis that the lower European productivity performance in comparison with the US can be explained not only by a lower level of corporate R&D investment, but also by a lower capacity to translate R&D investment into productivity gains. The proposed microeconometric estimates are based on a unique longitudinal database covering the period 1990-2008 and comprising 1,809 US and European companies for a total of 16,079 observations. Consistent with previous literature, we find robust evidence of a significant impact of R&D on productivity; however – using different estimation techniques - the R&D coefficients for the US firms always turn out to be significantly higher. To see to what extent these transatlantic differences may be related to the different sectoral structures in the US and the EU, we differentiated the analysis by sectors. The result is that both in manufacturing, services and high-tech sectors US firms are more efficient in translating their R&D investments into productivity increases.R&D, productivity, embodied technological change, US, EU. JEL classification:O33

Anomalous BCS equation for a Luttinger superconductor

In the context of the Anderson theory of high T_c cuprates, we develop a BCS theory for Luttinger liquids. If the Luttinger interaction is much stronger than the BCS potential we find that the BCS equation is quite modified compared to usual BCS equation for Fermi liquids. In particular T_c predicted by the BCS equation for Luttinger liquids is quite higher than the usual T_c for Fermi liquids

Finite element analysis of forward extrusion of 1010 steel

Reliability of FE simulation of metal forming processes depends critically on the proper definition of material properties, the friction boundary conditions and details of the FE approach. To address these issues, the room temperature strain hardening behaviour of 1010 steel was established by performing a uniaxial compression test for the true strain of up to 1.5. Friction was evaluated using a ring test, with the two faces of the ring coated with a phosphate conversion layer and soap; the friction experimental results were matched with the FE established reference curves. The experimentally obtained material and friction input data were used in FE simulation, employing Arbitrary Lagrangian Eulerian adaptive meshing, to provide a valuable insight into the process of forward extrusion of an industrial component

Effect of parasympathetic stimulation on brain activity during appraisal of fearful expressions

Autonomic nervous system activity is an important component of human emotion. Mental processes influence bodily physiology, which in turn feeds back to influence thoughts and feelings. Afferent cardiovascular signals from arterial baroreceptors in the carotid sinuses are processed within the brain and contribute to this two-way communication with the body. These carotid baroreceptors can be stimulated non-invasively by externally applying focal negative pressure bilaterally to the neck. In an experiment combining functional neuroimaging (fMRI) with carotid stimulation in healthy participants, we tested the hypothesis that manipulating afferent cardiovascular signals alters the central processing of emotional information (fearful and neutral facial expressions). Carotid stimulation, compared with sham stimulation, broadly attenuated activity across cortical and brainstem regions. Modulation of emotional processing was apparent as a significant expression-by-stimulation interaction within left amygdala, where responses during appraisal of fearful faces were selectively reduced by carotid stimulation. Moreover, activity reductions within insula, amygdala, and hippocampus correlated with the degree of stimulation-evoked change in the explicit emotional ratings of fearful faces. Across participants, individual differences in autonomic state (heart rate variability, a proxy measure of autonomic balance toward parasympathetic activity) predicted the extent to which carotid stimulation influenced neural (amygdala) responses during appraisal and subjective rating of fearful faces. Together our results provide mechanistic insight into the visceral component of emotion by identifying the neural substrates mediating cardiovascular influences on the processing of fear signals, potentially implicating central baroreflex mechanisms for anxiolytic treatment targets

"Debating as a classroom tool for adapting learning outcomes to the European higher education area"

The creation of the European Higher Education Area has meant a number of significant changes to the educational structures of the university community. In particular, the new system of European credits has generated the need for innovation in the design of curricula and teaching methods. In this paper, we propose debating as a classroom tool that can help fulfill these objectives by promoting an active student role in learning. To demonstrate the potential of this tool, a classroom experiment was conducted in a bachelor’s degree course in Industrial Economics (Regulation and Competition), involving a case study in competition policy and incorporating the techniques of a conventional debate (presentation of standpoints, turns, right to reply and summing up). The experiment yielded gains in student attainment and positive assessments of the subject. In conclusion, the incorporation of debating activities helps students to acquire the skills, be they general or specific, required to graduate successfully in Economics.European Higher Education Area; Debating; Industrial Organization; Academic Success; European Credit Transfer System. JEL classification:A23, B4, I2.

The regional distribution of unemployment: What do micro-data tell us?

Regional disparities in unemployment rates are large and persistent. The literature provides evidence of their magnitude and evolution, as well as evidence of the role of certain economic, demographic and environmental factors in explaining the gap between regions of low and high unemployment. Most of these studies, however, adopt an aggregate approach and so do not account for the individual characteristics of the unemployed and employed in each region. This paper, by drawing on micro-data from the Spanish wave of the Labour Force Survey, seeks to remedy this shortcoming by analysing regional differentials in unemployment rates. An appropriate decomposition of the regional gap in the average probability of being unemployed enables us to distinguish between the contribution of differences in the regional distribution of individual characteristics from that attributable to a different impact of these characteristics on the probability of unemployment. Our results suggest that the well-documented disparities in regional unemployment are not just the result of regional heterogeneity in the distribution of individual characteristics. Non-negligible differences in the probability of unemployment remain after controlling for this type of heterogeneity, as a result of differences across regions in the impact of the observed characteristics. Among the factors considered in our analysis, regional differences in the endowment and impact of an individual's education are shown to play a major role

"The regional distribution of unemployment. What do micro-data tell us?"

Regional disparities in unemployment rates are large and persistent. The literature provides evidence of their magnitude and evolution, as well as evidence of the role of certain economic, demographic and environmental factors in explaining the gap between regions of low and high unemployment. Most of these studies, however, adopt an aggregate approach and so do not account for the individual characteristics of the unemployed and employed in each region. This paper, by drawing on micro-data from the Spanish wave of the Labour Force Survey, seeks to remedy this shortcoming by analysing regional differentials in unemployment rates. An appropriate decomposition of the regional gap in the average probability of being unemployed enables us to distinguish between the contribution of differences in the regional distribution of individual characteristics from that attributable to a different impact of these characteristics on the probability of unemployment. Our results suggest that the well-documented disparities in regional unemployment are not just the result of regional heterogeneity in the distribution of individual characteristics. Non-negligible differences in the probability of unemployment remain after controlling for this type of heterogeneity, as a result of differences across regions in the impact of the observed characteristics. Among the factors considered in our analysis, regional differences in the endowment and impact of an individual’s education are shown to play a major role.Regional labour markets, Regional unemployment, Education, Gap decomposition for non-linear models. JEL classification:C25, J64, J70, R23